A mechanism of topology optimization for underwater acoustic sensor networks based on autonomous underwater vehicles by Ming He, Fangxin Liu, Zhuang Miao, Huan Zhou, Qiuli Chen

“…To solve this problem, a topology optimization method, also called TO-A algorithm, is developed based on topology reconfiguration. …”
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Individual health passport storage, sharing and verification scheme based on blockchain by GAO Hancheng, JI Haoyu, GAO Chenhao, HUANG Haiping

“…The scheme also refined the weak consensus mechanism, with an improved algorithm that achieved consensus in merely two stages. …”
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Optimization of Processor Clock Frequency for Sensor Network Nodes Based on Energy Use and Timing Constraints by Youngmin Kim, Heeju Joo, Chan-Gun Lee

“…We analyze the extended model and verify that our algorithm calculates the clock frequency that optimizes energy savings while satisfying the timing constraints.…”
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OPTIMAL DISTRIBUTION NETWORK RECONFIGURATION FOR LOSS MINIMIZATION AND VOLTAGE PROFILE IMPROVEMENT BASED ON ARTIFICIAL INTELLIGENCE by Omar Muhammed Neda

“…The original version of the Dolphin Echolocation Optimization (DEO) algorithm is designed for solving continuous optimization issues only. …”
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Crossover operators for molecular graphs with an application to virtual drug screening by Nico Domschke, Bruno J. Schmidt, Thomas Gatter, Richard Golnik, Paul Eisenhuth, Fabian Liessmann, Jens Meiler, Peter F. Stadler

“…Abstract Genetic algorithms are a powerful method to solve optimization problems with complex cost functions over vast search spaces that rely in particular on recombining parts of previous solutions. …”
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GENERATING OF OPTIMAL QUANTIZATION LEVELS OF CONTROL CURRENTS FOR LINEAR STEPPING DRIVES OF PRECISION MOTION SYSTEMS by I. V. Dainiak, V. P. Oger, D. S. Tsitko, D. G. Begun

“…An algorithm for determination of optimal quantization levels of control currents of drive's phases has been developed in the paper; it minimizes an error of positioning that forms correction files for application of a control system in the software. …”
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Multi‐objective multi‐period optimal site and size of distributed generation along with network reconfiguration by Ghulam Abbas, Zhi Wu, Aamir Ali

“…To address the pointed‐out challenge of multiperiod optimal DG allocation and reconfiguration while simultaneously decreasing the cost of energy supplied, the cost of energy lost, and the voltage deviation, a novel Multi‐objective Bidirectional co‐evolutionary algorithm (BiCo) is implemented. …”
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Comprehensive Evaluation Method of Teaching Effect Based on Particle Swarm Optimization Neural Network Model by Heng Cao, Qianhui Gao

“…This paper studies the optimization algorithm and optimization system, it not only makes the algorithm involve basic mathematical operations, and the computer support required for the data processing process is not high, but it also improves the evaluation of the degree of optimization. …”
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Modeling and Optimization of the Multiobjective Stochastic Joint Replenishment and Delivery Problem under Supply Chain Environment by Lin Wang, Hui Qu, Shan Liu, Cai-xia Dun

“…Secondly, two approaches are designed to handle this complex multi-objective optimization problem. Linear programming (LP) approach converts the multi-objective to single objective, while a multi-objective evolution algorithm (MOEA) solves a multi-objective problem directly. …”
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Operational response to contamination in water distribution systems: a multi-objective Bayesian optimization approach by Khalid Alnajim, Ahmed A. Abokifa

“…The optimization framework aims to balance the conflicting objectives of minimizing response time while maximizing water quality metrics after contamination events. …”
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Research on the optimization method of emergency material post transportation model based on bi-level programming by Haixia ZHOU, Yurong MEI, Furu LYU, Zhixin SUN

“…Emergency logistics is a special logistics activity that protects the need of personnel,materials and funds in the event of a major emergency.In the post transportation model of emergency supplies,how to quickly and accurately deliver a large amount of rescue materials to the place of need is a huge challenge to emergency logistics.The logistics cost and the logistics time in the entire logistics process could be minimized by the bi-level planning method while meeting the demand for emergency supplies at the demand point.The bi-level programming model was constructed with the minimum logistics cost of the upper layer and the shortest logistics time of the bottom layer as the goal,and a hybrid tabu search genetic algorithm (HTSGA) was designed to solve the model,which solved the problem of emergency logistics transportation route optimization after the disaster.Finally,the experimental result comparison verified the effectiveness of the model and algorithm.…”
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Swarm based Heuristic Optimization of the Recurrent Customers and Standby Server Under General Retrial Times by N. Micheal Mathavavisakan, K. Indhira, Aliakbar Montazer Haghighi

“…The results revealed that these algorithms successfully minimized operational costs while maintaining optimal system efficiency. …”
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Optimizing low-power, anti-interference routing with IRS through spatiotemporal reinforcement and federated learning by Chengfu Fan, Shoujiu Xiong, Fei Zhou

“…Abstract This paper introduces the SAC-IRS algorithm, a novel approach that combines Intelligent Reflecting Surfaces (IRS) and Reinforcement Learning (RL) to optimize network performance, specifically targeting packet delivery rate and energy efficiency. …”
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Maritime Port Freight Flow Optimization with Underground Container Logistics Systems Under Demand Uncertainty by Miaomiao Sun, Chengji Liang, Yu Wang, Salvatore Antonio Biancardo

“…A stochastic optimization model is developed, incorporating transportation, environmental, carbon tax and subsidy, and congestion costs while satisfying various constraints, such as capacity limits, time constraints, and low-carbon transport requirements. …”
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Optimization of ore production scheduling strategy using NSGA-II-GRA in open-pit mining by ZhongQiang Chen, PingCheng Song, RunHan Liu, Qi Wang, YuMeng Shen

“…Abstract To address the challenges posed by ore grade fluctuations, extraction cost variations, and market price instability in open-pit ore production strategies, an optimization model integrating a solution algorithm integrating dynamic simulation is proposed. …”
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Performance optimization of active RIS-assisted near-shore dual-function radar communicaiton system by XU Miao, YUE Dianwu, SUN Yu, WU Xiangkai, YUAN Meng

“…In order to align with the characteristics of maritime channels, a three-path loss model and a two wave with diffuse power (TWDP) channel considering the evaporative duct over the sea was employed. An alternating optimization algorithm based on fractional programming theory and the Lagrangian operator method was proposed. …”
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Research on Feature Extraction Method and Process Optimization of Rolling Bearing Faults Based on Electrostatic Monitoring by Ruochen Liu, Han Yin, Jianzhong Sun, Lanchun Zhang

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Coverage optimization and node minimization in WSNs: an enhanced hybrid PSO approach with spatial position encoding by Yinghua Tong, Lianhai Lin, Liqin Tian, Zhigang Wang, Wenxing Wu, Junyi Wu

“…This paper presents an enhanced hybrid particle swarm optimization (EHPSO) algorithm that incorporates a spatial position encoding (SPE) strategy to optimize coverage while dynamically adjusting the number of sensors deployed in WSNs. …”
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Information-Driven Model Predictive Control With Adaptive Partitioning for Energy Optimization in Automated Electric Vehicles by Shahriar Shahram, Yaser P. Fallah

“…These convex models are integrated into the MPC to compute optimal control inputs that minimize energy consumption while satisfying vehicle dynamics and constraints. …”
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Swarm intelligence for energy-efficient heating, ventilation, and air conditioning (HVAC) systems: A case study in smart buildings by Vinoth Kanna I, Raja Subramani, Maher Ali Rusho, Shubham Sharma, Ramachandran T, Abinash Mahapatro, Deepak Gupta, Jasmina Lozanovic

“…This research utilizes swarm intelligence algorithms—Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and hybrid PSO-ACO-to optimize energy efficiency and thermal comfort in smart building HVAC systems. …”
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